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Inexact Bayesian point pattern matching for linear transformations

Christmas, J., Everson, R. M., Bell, James Stephen and Winlove, C. P. 2014. Inexact Bayesian point pattern matching for linear transformations. Pattern Recognition 47 (10) , pp. 3265-3275. 10.1016/j.patcog.2014.04.022

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Abstract

We introduce a novel Bayesian inexact point pattern matching model that assumes that a linear transformation relates the two sets of points. The matching problem is inexact due to the lack of one-to-one correspondence between the point sets and the presence of noise. The algorithm is itself inexact; we use variational Bayesian approximation to estimate the posterior distributions in the face of a problematic evidence term. The method turns out to be similar in structure to the iterative closest point algorithm.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Optometry and Vision Sciences
Publisher: Elsevier
ISSN: 0031-3203
Date of Acceptance: 26 April 2014
Last Modified: 25 Feb 2019 11:59
URI: http://orca.cf.ac.uk/id/eprint/86064

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